如何在R数据帧中将NaN转换为NA？
要将NaN转换为R数据帧中的NA，我们可以使用单个方括号将NaN值设置为NA值。首先，我们需要访问包含NaN值的列，然后使用访问NaN值，is.nan然后可以将这些值设置为NA，如以下示例所示。
考虑以下数据帧-
示例
x1<-sample(c(1,2,5,NaN),20,replace=TRUE) x2<-rpois(20,2) df1<-data.frame(x1,x2) df1输出结果
x1 x2 1 5 1 2 1 2 3 5 3 4 NaN 2 5 5 1 6 5 2 7 NaN 1 8 5 4 9 5 2 10 2 0 11 NaN 0 12 1 0 13 NaN 4 14 1 2 15 5 1 16 1 2 17 2 2 18 5 0 19 2 1 20 5 1
在df1的x1列中用NA替换NaN-
示例
df1$x1[is.nan(df1$x1)]<-NA df1输出结果
x1 x2 1 5 1 2 1 2 3 5 3 4 NA 2 5 5 1 6 5 2 7 NA 1 8 5 4 9 5 2 10 2 0 11 NA 0 12 1 0 13 NA 4 14 1 2 15 5 1 16 1 2 17 2 2 18 5 0 19 2 1 20 5 1
示例
y1<-sample(c(rnorm(2),NaN),20,replace=TRUE) y2<-rnorm(20) y3<-rnorm(20) df2<-data.frame(y1,y2,y3) df2输出结果
y1 y2 y3 1 -0.0867355 -1.28729227 -0.20581922 2 NaN 1.11408057 0.56750161 3 NaN 0.47302790 -0.72410253 4 NaN -0.34217866 0.33855658 5 NaN -2.52516598 0.78809964 6 -0.0867355 -0.65268724 -0.04150251 7 -0.0867355 0.42845639 -0.12955272 8 -0.0867355 0.71995182 0.24011099 9 -0.0867355 0.07829339 3.10334568 10 -0.9135175 0.07250105 -0.41307585 11 -0.0867355 1.58477752 0.96751855 12 NaN -1.84389126 -0.42843257 13 -0.0867355 -0.10860452 -0.32978319 14 -0.9135175 -1.25311587 -1.07537515 15 -0.0867355 0.58514141 2.05516953 16 NaN 2.02405825 0.18098639 17 -0.9135175 0.90327161 -0.22561346 18 -0.9135175 0.81260538 -1.98065156 19 NaN -1.60608848 -1.39970818 20 NaN -0.82239927 -1.45993348
在df2的y1列中用NA替换NaN-
示例
df2$y1[is.nan(df2$y1)]<-NA df2输出结果
y1 y2 y3 1 -0.0867355 -1.28729227 -0.20581922 2 NA 1.11408057 0.56750161 3 NA 0.47302790 -0.72410253 4 NA -0.34217866 0.33855658 5 NA -2.52516598 0.78809964 6 -0.0867355 -0.65268724 -0.04150251 7 -0.0867355 0.42845639 -0.12955272 8 -0.0867355 0.71995182 0.24011099 9 -0.0867355 0.07829339 3.10334568 10 -0.9135175 0.07250105 -0.41307585 11 -0.0867355 1.58477752 0.96751855 12 NA -1.84389126 -0.42843257 13 -0.0867355 -0.10860452 -0.32978319 14 -0.9135175 -1.25311587 -1.07537515 15 -0.0867355 0.58514141 2.05516953 16 NA 2.02405825 0.18098639 17 -0.9135175 0.90327161 -0.22561346 18 -0.9135175 0.81260538 -1.98065156 19 NA -1.60608848 -1.39970818 20 NA -0.82239927 -1.45993348